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Yu WANG Liangyong YANG Jilian ZHANG Xuelian DENG
Cloud computing has become the mainstream computing paradigm nowadays. More and more data owners (DO) choose to outsource their data to a cloud service provider (CSP), who is responsible for data management and query processing on behalf of DO, so as to cut down operational costs for the DO. However, in real-world applications, CSP may be untrusted, hence it is necessary to authenticate the query result returned from the CSP. In this paper, we consider the problem of approximate string query result authentication in the context of database outsourcing. Based on Merkle Hash Tree (MHT) and Trie, we propose an authenticated tree structure named MTrie for authenticating approximate string query results. We design efficient algorithms for query processing and query result authentication. To verify effectiveness of our method, we have conducted extensive experiments on real datasets and the results show that our proposed method can effectively authenticate approximate string query results.
Hasan KADHEM Toshiyuki AMAGASA Hiroyuki KITAGAWA
Encryption can provide strong security for sensitive data against inside and outside attacks. This is especially true in the "Database as Service" model, where confidentiality and privacy are important issues for the client. In fact, existing encryption approaches are vulnerable to a statistical attack because each value is encrypted to another fixed value. This paper presents a novel database encryption scheme called MV-OPES (Multivalued--Order Preserving Encryption Scheme), which allows privacy-preserving queries over encrypted databases with an improved security level. Our idea is to encrypt a value to different multiple values to prevent statistical attacks. At the same time, MV-OPES preserves the order of the integer values to allow comparison operations to be directly applied on encrypted data. Using calculated distance (range), we propose a novel method that allows a join query between relations based on inequality over encrypted values. We also present techniques to offload query execution load to a database server as much as possible, thereby making a better use of server resources in a database outsourcing environment. Our scheme can easily be integrated with current database systems as it is designed to work with existing indexing structures. It is robust against statistical attack and the estimation of true values. MV-OPES experiments show that security for sensitive data can be achieved with reasonable overhead, establishing the practicability of the scheme.